Gen2 RGB相机上的空间对象跟踪器 ================================= 本示例说明如何在RGB输入帧上运行MobileNetv2SSD，以及如何对人员执行空间对象跟踪。 演示 ***************** 设置 ******************** .. warning:: 说明：此处安装的是第二代depthai库 请运行以下命令来安装所需的依赖项 .. code-block:: bash python3 -m pip install -U pip python3 -m pip install opencv-python python3 -m pip install -U --force-reinstall depthai 有关更多信息，请参阅 :ref:`Python API 安装指南 ` 这个示例还需要 mobileenetsdd blob ( :code:`mobilenet.blob` 文件 )才能工作——您可以从 `这里 `_ 下载它。 源代码 ********************* 可以在 `GitHub `_ 上找到。国内用户也可以在 `gitee `_ 上找到。 .. code-block:: python #!/usr/bin/env python3 from pathlib import Path import cv2 import depthai as dai import numpy as np import time import argparse labelMap = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"] nnPathDefault = str((Path(__file__).parent / Path('models/mobilenet-ssd_openvino_2021.2_6shave.blob')).resolve().absolute()) parser = argparse.ArgumentParser() parser.add_argument('nnPath', nargs='?', help="Path to mobilenet detection network blob", default=nnPathDefault) parser.add_argument('-ff', '--full_frame', action="store_true", help="Perform tracking on full RGB frame", default=False) args = parser.parse_args() fullFrameTracking = args.full_frame # 开始定义管道 pipeline = dai.Pipeline() colorCam = pipeline.createColorCamera() spatialDetectionNetwork = pipeline.createMobileNetSpatialDetectionNetwork() monoLeft = pipeline.createMonoCamera() monoRight = pipeline.createMonoCamera() stereo = pipeline.createStereoDepth() objectTracker = pipeline.createObjectTracker() xoutRgb = pipeline.createXLinkOut() trackerOut = pipeline.createXLinkOut() xoutRgb.setStreamName("preview") trackerOut.setStreamName("tracklets") colorCam.setPreviewSize(300, 300) colorCam.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P) colorCam.setInterleaved(False) colorCam.setColorOrder(dai.ColorCameraProperties.ColorOrder.BGR) monoLeft.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P) monoLeft.setBoardSocket(dai.CameraBoardSocket.LEFT) monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P) monoRight.setBoardSocket(dai.CameraBoardSocket.RIGHT) # 设置节点配置 stereo.setConfidenceThreshold(255) spatialDetectionNetwork.setBlobPath(args.nnPath) spatialDetectionNetwork.setConfidenceThreshold(0.5) spatialDetectionNetwork.input.setBlocking(False) spatialDetectionNetwork.setBoundingBoxScaleFactor(0.5) spatialDetectionNetwork.setDepthLowerThreshold(100) spatialDetectionNetwork.setDepthUpperThreshold(5000) # 创建输出流 monoLeft.out.link(stereo.left) monoRight.out.link(stereo.right) # 连接插件 CAM . NN . XLINK colorCam.preview.link(spatialDetectionNetwork.input) objectTracker.passthroughTrackerFrame.link(xoutRgb.input) objectTracker.setDetectionLabelsToTrack([15]) # 只追踪人 # 可能的跟踪类型：ZERO_TERM_COLOR_HISTOGRAM，ZERO_TERM_IMAGELESS objectTracker.setTrackerType(dai.TrackerType.ZERO_TERM_COLOR_HISTOGRAM) # 跟踪新对象时采用最小的ID，可能的选项：SMALLEST_ID，UNIQUE_ID objectTracker.setTrackerIdAssigmentPolicy(dai.TrackerIdAssigmentPolicy.SMALLEST_ID) objectTracker.out.link(trackerOut.input) if fullFrameTracking: colorCam.setPreviewKeepAspectRatio(False) colorCam.video.link(objectTracker.inputTrackerFrame) objectTracker.inputTrackerFrame.setBlocking(False) # 如果全帧速度太慢，请不要阻塞管道 objectTracker.inputTrackerFrame.setQueueSize(2) else: spatialDetectionNetwork.passthrough.link(objectTracker.inputTrackerFrame) spatialDetectionNetwork.passthrough.link(objectTracker.inputDetectionFrame) spatialDetectionNetwork.out.link(objectTracker.inputDetections) stereo.depth.link(spatialDetectionNetwork.inputDepth) # 连接并启动管道 with dai.Device(pipeline) as device: preview = device.getOutputQueue("preview", 4, False) tracklets = device.getOutputQueue("tracklets", 4, False) startTime = time.monotonic() counter = 0 fps = 0 frame = None while(True): imgFrame = preview.get() track = tracklets.get() counter+=1 current_time = time.monotonic() if (current_time - startTime) > 1 : fps = counter / (current_time - startTime) counter = 0 startTime = current_time color = (255, 0, 0) frame = imgFrame.getCvFrame() trackletsData = track.tracklets for t in trackletsData: roi = t.roi.denormalize(frame.shape[1], frame.shape[0]) x1 = int(roi.topLeft().x) y1 = int(roi.topLeft().y) x2 = int(roi.bottomRight().x) y2 = int(roi.bottomRight().y) try: label = labelMap[t.label] except: label = t.label cv2.putText(frame, str(label), (x1 + 10, y1 + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, f"ID: {[t.id]}", (x1 + 10, y1 + 35), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, t.status.name, (x1 + 10, y1 + 50), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.rectangle(frame, (x1, y1), (x2, y2), color, cv2.FONT_HERSHEY_SIMPLEX) cv2.putText(frame, f"X: {int(t.spatialCoordinates.x)} mm", (x1 + 10, y1 + 65), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, f"Y: {int(t.spatialCoordinates.y)} mm", (x1 + 10, y1 + 80), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, f"Z: {int(t.spatialCoordinates.z)} mm", (x1 + 10, y1 + 95), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, "NN fps: {:.2f}".format(fps), (2, frame.shape[0] - 4), cv2.FONT_HERSHEY_TRIPLEX, 0.4, color) cv2.imshow("tracker", frame) if cv2.waitKey(1) == ord('q'): break .. include:: /pages/includes/footer-short.rst